LAPSE:2021.0385
Published Article
LAPSE:2021.0385
Performance Evaluation for a Sustainable Supply Chain Management System in the Automotive Industry Using Artificial Intelligence
Oana Dumitrascu, Manuel Dumitrascu, Dan Dobrotǎ
May 24, 2021
Increasing the sustainability of a system can be achieved by evaluating the system, identifying the issues and their root cause and solving them. Performance evaluation translates into key performance indicators (KPIs) with a high impact on increasing overall efficacy and efficiency. As the pool of KPIs has increased over time in the context of evaluating the supply chain management (SCM) system’s performance and assessing, communicating and managing its risks, a mathematical model based on neural networks has been developed. The SCM system has been structured into subsystems with the most relevant KPIs for set subsystems and their most important contributions on the increase in the overall SCM system performance and sustainability. As a result of the performed research based on the interview method, the five most relevant KPIs of each SCM subsystem and the most relevant problems are underlined. The main goal of this paper is to develop a performance evaluation model that links specific problems with the most relevant KPIs for every subsystem of the supply chain management. This paper demonstrates that by using data mining, the relationship between certain problems that appear in the supply chain management of every company and specific KPIs can be identified. The paper concludes with a graphical user interface (GUI) based on neural networks using the multilayer perceptron artificial intelligence algorithm where the most trustworthy KPIs for each selected problem can be predicted. This aspect provides a highly innovative contribution in solving supply chain management problems provided by organizations by allowing them to holistically track, communicate, analyze and improve the SCM system and ensure overall system sustainability.
Keywords
Artificial Intelligence, data mining, key performance indicator, neural network, performance evaluation, risk management
Suggested Citation
Dumitrascu O, Dumitrascu M, Dobrotǎ D. Performance Evaluation for a Sustainable Supply Chain Management System in the Automotive Industry Using Artificial Intelligence. (2021). LAPSE:2021.0385
Author Affiliations
Dumitrascu O: Industrial Machines and Equipment Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, 550025 Sibiu, Romania [ORCID]
Dumitrascu M: Industrial Machines and Equipment Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, 550025 Sibiu, Romania
Dobrotǎ D: Industrial Machines and Equipment Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, 550025 Sibiu, Romania [ORCID]
Journal Name
Processes
Volume
8
Issue
11
Article Number
E1384
Year
2020
Publication Date
2020-10-30
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr8111384, Publication Type: Journal Article
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LAPSE:2021.0385
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doi:10.3390/pr8111384
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May 24, 2021
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CC BY 4.0
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[v1] (Original Submission)
May 24, 2021
 
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May 24, 2021
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http://psecommunity.org/LAPSE:2021.0385
 
Original Submitter
Calvin Tsay
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